basic cv2 piece

dependencies/Dockerfile_opencv

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+# Use the base image
+FROM ghcr.io/tauffer-consulting/domino-base-piece:latest
+
+# Update package lists and install necessary dependencies
+RUN apt-get update && \
+    apt-get install -y \
+    python3-dev \
+    python3-pip \
+    libopencv-dev
+
+# Install OpenCV using pip (Python package manager)
+RUN pip3 install opencv-python-headless
+
+# Set working directory (optional)
+WORKDIR /app

pieces/OpenCVSegmentationPiece/metadata.json

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+{
+    "name": "OpenCVFilterPiece",
+    "description": "Piece that uses OpenCV filter on an Image",
+    "dependency": {
+        "dockerfile": "Dockerfile_opencv"
+    },
+    "tags": [
+        "image",
+        "processing",
+        "filter"
+    ],
+    "style": {
+        "node_label": "OpenCV Filter Piece",
+        "node_style": {
+            "backgroundColor": "#38b2be"
+        },
+        "icon_class_name": "material-symbols:image-outline"
+    }
+}

pieces/OpenCVSegmentationPiece/models.py

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+from pydantic import BaseModel, Field
+from enum import Enum
+
+class FilterNaem(str, Enum):
+    canny = "canny"
+    binary = "binary"
+
+class InputModel(BaseModel):
+    image_path: str = Field(
+        title="Image Path",
+        description="The path to the image to apply filter.",
+        json_schema_extra={"from_upstream": "always"}
+    )
+    filter_name: FilterNaem = Field(
+        title="Filter Name",
+        description="The name of the filter to apply.",
+        default="canny",
+    )
+
+
+class OutputModel(BaseModel):
+    image_path: str = Field(
+        title="Output image Path",
+        description="The path to the image with the filter applied.",
+    )

pieces/OpenCVSegmentationPiece/piece.py

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+from domino.base_piece import BasePiece
+from .models import InputModel, OutputModel
+import pandas as pd
+from pathlib import Path
+from plotly.subplots import make_subplots
+import cv2
+from pathlib import Path
+
+
+class OpenCVFilterPiece(BasePiece):
+
+    def piece_function(self, input_data: InputModel):
+        image = cv2.imread(input_data.image_path)
+        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+        if input_data.filter_name == "canny":
+            edged = cv2.Canny(gray, 50, 100)
+        elif input_data.filter_name == "binary":
+            _, edged = cv2.threshold(gray, 100, 255, cv2.THRESH_BINARY)
+        else:
+            raise ValueError(f"Unknown filter name: {input_data.filter_name}")
+
+        output_image_path = Path(self.results_path) / "opencv_image.png"
+        cv2.imwrite(str(output_image_path), edged)
+        self.display_result = {
+            "file_type": "png",
+            "file_path": str(output_image_path)
+        }
+
+        return OutputModel(
+            image_path=str(output_image_path)
+        )
+
+